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Aligning extracted LC-MS peak lists via density maximization
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Perera, Venura, De Torres Zabala, Marta, Florance, Hannah, Smirnoff, Nicholas, Grant, Murray and Yang, Zheng Rong (2012) Aligning extracted LC-MS peak lists via density maximization. Metabolomics, 8 (S1). pp. 175-185. doi:10.1007/s11306-011-0389-x ISSN 1573-3882.
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Official URL: http://dx.doi.org/10.1007/s11306-011-0389-x
Abstract
Rapid improvements in mass spectrometry sensitivity and mass accuracy combined with improved liquid chromatography separation technologies allow acquisition of high throughput metabolomics data, providing an excellent opportunity to understand biological processes. While spectral deconvolution software can identify discrete masses and their associated isotopes and adducts, the utility of metabolomic approaches for many statistical analyses such as identifying differentially abundant ions depends heavily on data quality and robustness, especially, the accuracy of aligning features across multiple biological replicates. We have developed a novel algorithm for feature alignment using density maximization. Instead of a greedy iterative, hence local, merging strategy, which has been widely used in the literature and in commercial applications, we apply a global merging strategy to improve alignment quality. Using both simulated and real data, we demonstrate that our new algorithm provides high map (e.g. chromatogram) coverage, which is critically important for non-targeted comparative metabolite profiling of highly replicated biological datasets.
| Item Type: | Journal Article | ||||
|---|---|---|---|---|---|
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) | ||||
| Journal or Publication Title: | Metabolomics | ||||
| Publisher: | Springer New York LLC | ||||
| ISSN: | 1573-3882 | ||||
| Official Date: | 2012 | ||||
| Dates: |
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| Volume: | 8 | ||||
| Number: | S1 | ||||
| Page Range: | pp. 175-185 | ||||
| DOI: | 10.1007/s11306-011-0389-x | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Restricted or Subscription Access |
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